Image Processing Applications with a PCNN. - Mario Ignacio Chacon Murguia; Alejandro S. Zimmerman; Pablo Rivas-Perea (ISNN (3), 2007)

A Fuzzy Clustering Approach for Face Recognition Based on Face Feature Lines and Eigenvectors. - Mario Ignacio Chacon Murguia; Pablo Rivas-Perea; Graciela Ramírez Alonso (Eng. Lett., 2007)

Mobile robot for face recognition: A collaborative environment. - Pablo Rivas-Perea; José-Gerardo Rosiles; Omar Velarde Anaya; Leonardo Valencia Olvera; Luis Humberto Uribe Chavira; Mario I. Chacon (HPCS, 2009)

Self organizing maps for class discovery in the quantitative colocalization analysis feature space. - Pablo Rivas-Perea; José-Gerardo Rosiles; Wei Qian (IJCNN, 2009)

Automatic Dust Storm Detection Based on Supervised Classification of Multispectral Data. - Pablo Rivas-Perea; José-Gerardo Rosiles; Mario Ignacio Chacon Murguia; James Tilton (Soft Computing for Recognition Based on Biometrics, 2010)

Dust Storm Detection Using a Neural Network with Uncertainty and Ambiguity Output Analysis. - Mario Ignacio Chacon Murguia; Yearim Quezada-Holguín; Pablo Rivas-Perea; Sergio D. Cabrera (MCPR, 2011)

Subjective Colocalization Analysis with Fuzzy Predicates. - Pablo Rivas-Perea; José-Gerardo Rosiles; Wei Qian (Soft Computing for Intelligent Control and Mobile Robotics, 2011)

A Low-Complexity Geometric Bilateration Method for Localization in Wireless Sensor Networks and Its Comparison with Least-Squares Methods. - Juan Cota-Ruiz; José-Gerardo Rosiles; Ernesto Sifuentes; Pablo Rivas-Perea (Sensors, 2012)

An algorithm for training a large scale support vector machine for regression based on linear programming and decomposition methods. - Pablo Rivas-Perea; Juan Cota-Ruiz (Pattern Recognit. Lett., 2013)

Corrigendum to "An algorithm for training a large scale support vector machine for regression based on linear programming and decomposition methods" [Pattern Recognition Lett. 34(4) (2013) 439-451]. - Pablo Rivas-Perea; Juan Cota-Ruiz; José-Gerardo Rosiles (Pattern Recognit. Lett., 2013)

A Convolutional Neural Network approach for classifying leukocoria. - Ryan Henning; Pablo Rivas-Perea; Bryan Shaw; Greg Hamerly (SSIAI, 2014)

Finding the smallest circle containing the iris in the denoised wavelet domain. - Pablo Rivas-Perea; Ryan Henning; Bryan Shaw; Greg Hamerly (SSIAI, 2014)

A nonlinear least squares quasi-Newton strategy for LP-SVR hyper-parameters selection. - Pablo Rivas-Perea; Juan Cota-Ruiz; José-Gerardo Rosiles (Int. J. Mach. Learn. Cybern., 2014)

Entrenamiento de una red neuronal para el reconocimiento de imagenes de lengua de senas capturadas con sensores de profundidad. - Pedro E. Rivas P.; Omar Velarde Anaya; Samuel González López; Pablo Rivas-Perea; Norma Angelica Alvarez-Torres (CoRR, 2018)

Modeling Five Sentence Quality Representations by Finding Latent Spaces Produced with Deep Long Short-Memory Models. - Pablo Rivas 001 (WNLP@ACL, 2019)

Government AI Readiness Meta-Analysis for Latin America And The Caribbean. - Laura N. Montoya; Pablo Rivas 001 (ISTAS, 2019)

Machine Learning for DDoS Attack Classification Using Hive Plots. - Pablo Rivas 001; Casimer M. DeCusatis; Matthew Oakley; Alex Antaki; Nicholas Blaskey; Steven LaFalce; Stephen Stone (UEMCON, 2019)

AI Orthopraxy: Towards a Framework for That Promotes Fairness. - Pablo Rivas 001 (ISTAS, 2020)

Developing Use Cases to Support an Empathic Technology Ethics Standard. - Randy Soper; Karen Bennet; Pablo Rivas 001; Mathana (ISTAS, 2020)

Accelerating the Training of an LP-SVR Over Large Datasets. - Pablo Rivas-Perea (SGAI Conf., 2020)

Towards Adversarially Robust DDoS-Attack Classification. - Michael Guarino; Pablo Rivas 001; Casimer M. DeCusatis (UEMCON, 2020)

Working Set Selection to Accelerate SVR Training. - Pablo Rivas 001 (AIDBEI, 2021)

Modeling SQL Statement Correctness with Attention-Based Convolutional Neural Networks. - Pablo Rivas 001; Donald R. Schwartz (CSCI, 2021)

Hybrid Quantum Variational Autoencoders for Representation Learning. - Pablo Rivas 001; Liang Zhao; Javier Orduz (CSCI, 2021)

Human Activity Classification Using Basic Machine Learning Models. - Bikram Khanal; Pablo Rivas 001; Javier Orduz (CSCI, 2021)

Quantum Machine Learning: A Case Study of Grover's Algorithm. - Bikram Khanal; Pablo Rivas 001; Javier Orduz; Alibek Zhakubayev (CSCI, 2021)

On the Practical Uses of Experimental Adversarial Neural Cryptography. - Korn Sooksatra; Pablo Rivas 001 (CSCI, 2021)

Adversarial Training Negatively Affects Fairness. - Korn Sooksatra; Pablo Rivas 001 (CSCI, 2021)

Evaluating Accuracy and Adversarial Robustness of Quanvolutional Neural Networks. - Korn Sooksatra; Pablo Rivas 001; Javier Orduz (CSCI, 2021)

Enhancing the Resolution of Satellite Imagery Using a Generative Model. - Mahee Noor Tayba; Pablo Rivas 001 (CSCI, 2021)

An Adversarial Neural Cryptography Approach to Integrity Checking: Learning to Secure Data Communications. - Korn Sooksatra; Pablo Rivas 001 (IJCNN, 2021)

Enhancing Adversarial Examples on Deep Q Networks with Previous Information. - Korn Sooksatra; Pablo Rivas 001 (SSCI, 2021)

On Unsupervised Reconstruction with Dressed Multilayered Variational Quantum Circuits. - Pablo Rivas 001; Liang Zhao (CSCI, 2022)

Unsupervised Machine Learning Methods for Diagnosing Autism Spectrum Disorder Using Multimodal Data: A Survey. - Antika Roy; Pablo Rivas 001; Mahee Noor Tayba (CSCI, 2022)

Artificial Intelligence Computing at the Quantum Level. - Olawale Ayoade; Pablo Rivas-Perea; Javier Orduz (Data, 2022)

Evaluation of adversarial attacks sensitivity of classifiers with occluded input data. - Korn Sooksatra; Pablo Rivas 001 (Neural Comput. Appl., 2022)

Navigating an Interdisciplinary Approach to Cybercrime Research. - Laurie Giddens; Stacie Petter; Gisela Bichler; Pablo Rivas 001; Michael H. Fullilove; Tomás Cerný (HICSS, 2023)

Evaluating Robustness of Reconstruction Models with Adversarial Networks. - Korn Sooksatra; Gissella Bejarano; Pablo Rivas 001 (INNS DLIA@IJCNN, 2023)

A Comparative Evaluation of Image Caption Synthesis Using Deep Neural Network. - Sadia Nasrin Tisha; Md Shahidur Rahaman; Pablo Rivas 001 (SDSC, 2023)

Combatting Human Trafficking in the Cyberspace: A Natural Language Processing-Based Methodology to Analyze the Language in Online Advertisements. - Alejandro Rodríguez Pérez; Pablo Rivas 001 (CoRR, 2023)

Mitigating Algorithmic Bias on Facial Expression Recognition. - Glauco A. Amigo; Pablo Rivas-Perea; Robert J. Marks II (CoRR, 2023)

Supercomputing leverages quantum machine learning and Grover's algorithm. - Bikram Khanal; Javier Orduz; Pablo Rivas 001; Erich Baker (J. Supercomput., 2023)

Automated Synthesis of Distributed Code from Sequential Snippets Using Deep Learning. - Arun Sanjel; Bikram Khanal; Pablo Rivas 001; Greg Speegle (IEEE Big Data, 2024)

Resilient Word-Embedding Alignment for BERT with Character-Based Layer in Noisy Environments. - Korn Sooksatra; Alejandro Rodríguez Pérez; Pablo Rivas 001 (IJCNN, 2024)

Using Static Analysis to Aid Monolith to Microservice System Transformation: Tuning Fuzzy c-Means in a VAE-Based GNN Approach. - Korn Sooksatra; Md Showkat Hossain Chy; Muhmmad Ashfakur Rahman Arju; Tomás Cerný; Pablo Rivas 001 (ASE Workshops, 2024)

Legal Natural Language Processing From 2015 to 2022: A Comprehensive Systematic Mapping Study of Advances and Applications. - Ernesto Quevedo; Tomás Cerný; Alejandro Rodriguez; Pablo Rivas 001; Jorge Yero; Korn Sooksatra; Alibek Zhakubayev; Davide Taibi 001 (IEEE Access, 2024)

A Modified Depolarization Approach for Efficient Quantum Machine Learning. - Bikram Khanal; Pablo Rivas 001 (CoRR, 2024)

A Review on Machine Learning Algorithms for Dust Aerosol Detection using Satellite Data. - Nurul Rafi; Pablo Rivas 001 (CoRR, 2024)

Is ReLU Adversarially Robust? - Korn Sooksatra; Greg Hamerly; Pablo Rivas 001 (CoRR, 2024)

On Adversarial Examples for Text Classification by Perturbing Latent Representations. - Korn Sooksatra; Bikram Khanal; Pablo Rivas 001 (CoRR, 2024)

On the Challenges of Creating Datasets for Analyzing Commercial Sex Advertisements to Assess Human Trafficking Risk and Organized Activity. - Pablo Rivas 001; Tomás Cerný; Alejandro Rodríguez Pérez; Javier Turek; Laurie Giddens; Gisela Bichler; Stacie Petter (CoRR, 2024)

Efficacy of ByT5 in Multilingual Translation of Biblical Texts for Underrepresented Languages. - Corinne Aars; Lauren Adams; Xiaokan Tian; Zhaoyu Wang; Colton Wismer; Jason Wu; Pablo Rivas 001; Korn Sooksatra; Matthew Fendt (CoRR, 2024)

Detecting Hallucinations in Large Language Model Generation: A Token Probability Approach. - Ernesto Quevedo; Jorge Yero; Rachel Koerner; Pablo Rivas 001; Tomás Cerný (CoRR, 2024)

A Review of Pulse-Coupled Neural Network Applications in Computer Vision and Image Processing. - Nurul Rafi; Pablo Rivas 001 (CoRR, 2024)

An Automated SQL Query Grading System Using An Attention-Based Convolutional Neural Network. - Donald R. Schwartz; Pablo Rivas 001 (CoRR, 2024)

AI Safety in Practice: Enhancing Adversarial Robustness in Multimodal Image Captioning. - Maisha Binte Rashid; Pablo Rivas 001 (CoRR, 2024)

Image-Based Leopard Seal Recognition: Approaches and Challenges in Current Automated Systems. - Jorge Yero Salazar; Pablo Rivas 001; Renato Borras-Chavez; Sarah Kienle (CoRR, 2024)

Bottleneck-based Encoder-decoder ARchitecture (BEAR) for Learning Unbiased Consumer-to-Consumer Image Representations. - Pablo Rivas 001; Gisela Bichler; Tomás Cerný; Laurie Giddens; Stacie Petter (CoRR, 2024)

Generalization Error Bound for Quantum Machine Learning in NISQ Era - A Survey. - Bikram Khanal; Pablo Rivas 001; Arun Sanjel; Korn Sooksatra; Ernesto Quevedo; Alejandro Rodríguez Pérez (CoRR, 2024)

Learning Robust Observable to Address Noise in Quantum Machine Learning. - Bikram Khanal; Pablo Rivas 001 (CoRR, 2024)

From Latent to Engine Manifolds: Analyzing ImageBind's Multimodal Embedding Space. - Andrew Hamara; Pablo Rivas 001 (CoRR, 2024)

NLP-Guided Synthesis: Transitioning from Sequential Programs to Distributed Programs. - Arun Sanjel; Bikram Khanal; Greg Speegle; Pablo Rivas 001 (CoRR, 2024)

Quantum-Enhanced Representation Learning: A Quanvolutional Autoencoder Approach against DDoS Threats. - Pablo Rivas 001; Javier Orduz; Tonni Das Jui; Casimer M. DeCusatis; Bikram Khanal (Mach. Learn. Knowl. Extr., 2024)

Fairness issues, current approaches, and challenges in machine learning models. - Tonni Das Jui; Pablo Rivas 001 (Int. J. Mach. Learn. Cybern., 2024)

Navigating the Multimodal Landscape: A Review on Integration of Text and Image Data in Machine Learning Architectures. - Maisha Binte Rashid; Md Shahidur Rahaman; Pablo Rivas 001 (Mach. Learn. Knowl. Extr., 2024)

Generalization error bound for quantum machine learning in NISQ era - a survey. - Bikram Khanal; Pablo Rivas 001; Arun Sanjel; Korn Sooksatra; Ernesto Quevedo; Alejandro Rodriguez (Quantum Mach. Intell., 2024)

Exploring Visual Embedding Spaces Induced by Vision Transformers for Online Auto Parts Marketplaces. - Cameron Armijo; Pablo Rivas 001 (CoRR, 2025)

A Framework for Evaluating Vision-Language Model Safety: Building Trust in AI for Public Sector Applications. - Maisha Binte Rashid; Pablo Rivas 001 (CoRR, 2025)

Leveraging OpenFlamingo for Multimodal Embedding Analysis of C2C Car Parts Data. - Maisha Binte Rashid; Pablo Rivas 001 (CoRR, 2025)

Data-dependent generalization bounds for parameterized quantum models under noise. - Bikram Khanal; Pablo Rivas 001 (J. Supercomput., 2025)

Neural Pruning for 3D Scene Reconstruction: Efficient NeRF Acceleration. - Tianqi Ding; Dawei Xiang; Pablo Rivas 001; Liang Dong (CoRR, 2025)

Learning to Plan via Supervised Contrastive Learning and Strategic Interpolation: A Chess Case Study. - Andrew Hamara; Greg Hamerly; Pablo Rivas 001; Andrew C. Freeman (CoRR, 2025)